PREditor Predictive RNA Editor for Plant Mitochondrial Genes

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PREditorPredictive RNA Editor for Plant
Mitochondrial Genes

• Jeff Mower

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• What is RNA Editing?
• A process that alters the RNA sequence
• Nt insertion, deletion, or conversion
• Does not include RNA maturation processes

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• RNA Editing in Plants
• Occurs in mitochondria and chloroplasts
• C to U and U to C conversions
• Mechanism is not known

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• RNA Editing in Plants
• In seed plants (conifers, flowering plants, etc.)
• Widespread in mitochondrion
• Rare in chloroplast
• Predominantly C to U
• In non-seed plants (mosses, ferns, etc.)
• Frequent in mitochondrion and chloroplast
• Both C to U and U to C are common

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AUG
UGA
CAA
AAU
CGU
UCU
UGC
GGC
GUA
AGACGGUC
UGGC
M R N S V G C
Q
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AUG
UGA
CAA
AAU
CGU
UCU
UGC
GGC
GUA
AGACGGUC
UGGC
M R N S V G C
Q
AUG
AUG
CAA
AAU
CGU
UCU
UGC
GGC
GUA
GUC
UGA
AG
UGGC
M V M R N S
V G C Q
Creation of new start codon
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AUG
UGA
CAA
AAU
CGU
UCU
UGC
GGC
GUA
AGACGGUC
UGGC
M R N S V G C
Q
AUG
AUG
CAA
AAU
UGU
UUU
UGC
GGC
GUA
GUC
UGA
AG
UGGC
M V M C N F
V G C Q
Alteration of protein sequence
Creation of new start codon
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AUG
UGA
CAA
AAU
CGU
UCU
UGC
GGC
GUA
AGACGGUC
UGGC
M R N S V G C
Q
AUG
AUG
CAA
AAU
UGU
UUU
UGC
GGU
GUA
GUC
UGA
AG
UGGC
M V M C N F
V G C Q
Alteration of protein sequence
Creation of new start codon
No effect on protein sequence
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AUG
UGA
CAA
AAU
CGU
UCU
UGC
GGC
GUA
AGACGGUC
UGGC
M R N S V G C
Q
AUG
AUG
UAA
AAU
UGU
UUU
UGC
GGU
GUA
GUC
UGAUGGC
AG
M V M C N F
V G C
Alteration of protein sequence
Creation of new stop codon
Creation of new start codon
No effect on protein sequence
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• Identifying Edit Sites
• Determine experimentally
• Need to isolate and reverse transcribe RNA
• Need multiple reads (editing is not always
  complete)

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• Identifying Edit Sites
• Determine experimentally
• Need to isolate and reverse transcribe RNA
• Need multiple reads (editing is not always
  complete)
• Predict based on sequence context
• Upstream and downstream regions are important
• Unambiguous motifs have not been identified

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• Identifying Edit Sites
• Determine experimentally
• Need to isolate and reverse transcribe RNA
• Need multiple reads (editing is not always
  complete)
• Predict based on sequence context
• Upstream and downstream regions are important
• Unambiguous motifs have not been identified
• Predict based on protein conservation
• Proteins are more conserved after editing
• Editing tends to correct amino acid sequences

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• PREditor Methodology
• Aligned sequence database (ASD) Construction
• 363 DNA sequences
• RNA editing information is known
• Organisms do not perform RNA editing
• Proteins were translated using the editing
  information
• Homologous proteins were aligned
• 42 different alignments
• All known mt proteins are covered

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• PREditor Methodology
• Input Sequence Manipulation
• Accept a protein-coding DNA sequence as input
• Translate input sequence
• Align translation to homologous proteins in ASD

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• PREditor Methodology
• The Underlying Principle
• ASD sequences translated from edited RNA
• Input sequence translated from unedited DNA
• Where can RNA editing in the input sequence
  increase conservation to the ASD sequences?

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• Performance Analysis
• Remove one protein sequence from the database
• Use the unedited DNA sequence as input
• Calculate statistics
• Accuracy (TP TN) / (TP FP TN FN)
• Sensitivity TP / (TP FN)
• Specificity TN / (TN FP)
• Repeat for each sequence

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• Performance Analysis
• Total Cs 58,982
• True edited sites 3,548 (6.0)
• TP 2,922
• FN 626
• True non-edited sites 55,434
• TN 54,829
• FP 605

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• Performance Analysis
• Sensitivity 82.4
• Proportion of true edited sites that were
  predicted correctly
• Increases to 94.6 if you ignore missed silent
  edited sites
• Specificity 98.9
• Proportion of true non-edited sites that were
  predicted correctly
• Accuracy 97.9
• Proportion of all sites that were predicted
  correctly
• Increases to 98.7 if you ignore missed silent
  edited sites

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• Limitations
• Cannot predict editing at silent sites
• 458 of 626 FN are at silent sites

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• Limitations
• Cannot predict editing at silent sites
• 458 of 626 FN are at silent sites
• Not a major problem in practice
• Silent editing sites do not affect the protein
  sequence
• Many silent sites are only occasionally edited
• Only 13 of editing sites are silent (expect
  38)

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• Limitations
• Aligned sequence database is skewed

Angiosperms 266 (74)
Gymnosperms 2 (1)
Origin of RNA editing
Ferns 0
Horsetails 0
Hornworts 0
Mosses 0
Liverworts 32 (9)
Charophytes 59 (16)
Chlorophytes ?
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• Limitations
• The skewed database effect

ASD1 Z
ASD2 Z
ASD3 Z
ASD4 Z
ASD4 X
Input X or Z?
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• Ongoing Work
• Reducing the skewed database effect
• Weighted sequences and phylogenetics

ASD1 Z
ASD2 Z
ASD3 Z
ASD4 Z
ASD4 X
Input X!
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• Ongoing Work
• Making the online resource more appealing
• Making the online resource more user-friendly

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• Future Directions
• Increase diversity in the ASD
• Analyze sequence context using the ASD
• Apply methodology to editing in chloroplasts
• Apply methodology to U to C editing

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• Thanks
• Jeff Palmer
• Sun Kim
• Danny Rice and other members of the Palmer lab